When Sensor and Actuator Networks Cover the World

John A. StankovicPresented by:

Sandeep reddy allu

The technologies for wireless communication, sensing, and computation are each progressing at faster and faster rates. Notably, they are also being combined for an amazingly large multiplicative effect. It can be envisioned that the world will eventually be covered by networks of networks of smart sensors and actuators. This fact will give rise to revolutionary applications. However, to make this vision a reality, many research challenges must be overcome. This paper describes a representative set of new applications and identifies several key research challenges.

Abstract

Wireless sensor and actuator networks (WSANs)

new technology with great potential for improving many current applications as well as creating new revolutionary systems in areas such as global scale environmental monitoring, precision agriculture, home and assisted living medical care, smart buildings and cities, industrial automation, and numerous military applications

WSANs - large numbers of minimal capacity sensing, computing, and communicating devices and various types of actuators .

These devices operate in complex and noisy real world, real-time environments

Introduction

Wsan Network sensor nodes

Embedded systems VS Real-time systems These both are highly related fields but not identical. embedded systems emphasize form factor, cost and other constraints, while real-time systems emphasize

timing properties.

Future Applications global scale environmental monitoring and

control social participatory computing, continuous birth-to-death health care.

At present a lot of sensors exist around the world .

These sensors focus mainly on single problem such as effect of tides on barrier islands off the coast of VA or tornado info in central part of USA.

These are separated by 100’s and 1000’s of meters .

In WSAN tech have potential of dense and flexible coverage with correlation across many WSAN’s . which leads to new understanding of environmental conditions. These are seperated by cms or mtrs.

Global Scale Environmental Monitoring and Control

This will help in micro agriculture to control pesticides and fertilizers usage amount.

When unexpected environmental disasters occur these sensors are used to collect immediate data which will help in rescue.

We can collect data from different lakes using this sensors and we can calculate the pollution effect on water bodies and also effect on fishes in those water bodies by performing data mining we can generate patterns which help in saving water life and also reduce water pollution.

When we have a global WSAN’s we will have a better understanding of how a particular change in weather at one place can effect others regions on earth

ubiquity of WSAN technology will include devices worn and carried by individuals as well as many emplaced systems in all our surroundings.

This access to real time data will effect the day to day schedule of human. Every individual will be able to track commuting delay s and minimize delays.

Traffic can be maintained by real time info from the sensors to reduce congestion .

This includes family groups, work groups, medical groups, and social groups. Preferences can be automatically incorporated into these activities. Automatic notifications for special social events such as a concert or sales on products currently of interest to an individual will be routine

This will lead to a Happier lifestyle.

Social Participatory Computing

WSANs can be implemented on large scale for medical care

We can create and maintain a separate account for each individual when they are born and there health position can be updated regularly by using sensors in cloths and instant treatment can be provided to the user when ever there is some change occurred health .

Long term health information on individuals will enable dramatic improvements in their care as well as over all understanding of a patient .

.This will improve health of every individual .

Continuous Birth-to-Death Health Care

From Raw Data to Knowledge: From world wide spread WSAN ‘s large amount of data is

collected continuously . But major task is to filter the data by implementing new

techniques to convert raw data to usable knowledge . Example: If we collect raw data from a person regarding his

diet ,respiration ,heart beat ,signs of depression etc we can convert this data to knowledge and we come to a decision about health of that person.

Other challenge is data interpretation and the formation of knowledge include addressing noisy physical world data and developing new inference techniques to filter data to improve confidence for data.

Challenges

Given that a very large number of WSANs will exist, with each providing many real time sensor streams, it will be common for a given stream of data to be used in many different ways for many different inference purposes.

But there no inference method which is 100 % correct. This uncertainty in interpreted data will cause user not to

trust on system. Trust is at the crux of next generation WSAN technology.

Security and privacy are essential elements of trust, and these are discussed in their own sections.

Without these basic underlying system-level capabilities, further inference might be operating with wrong or too much missing data, resulting in wrong conclusions. If these wrong conclusions drive actuators, then serious safety problems can occur. One approach is to ensure that all inferred information

is accompanied by a confidence level in the form of a probability that the information is correct or incorrect .

applications in WSNs typically initialize themselves by self-organizing after deployment

At the conclusion of the self-organizing stage, it is common for the nodes of a WSN to know their locations, have synchronized clocks, know their neighbors, and have a coherent set of parameter settings, such as consistent sleep/wake-up schedules, appropriate power levels for communication, and pair-wise security keys

DETERIORATION PROBLEM: deterioration problem is with clock synchronization.

Over time, clock drift causes nodes to have different enough times More and more nodes may become out of place over time to result

in application failures. Note that control of actuators can also deteriorate due to their

controlling software and protocols, but also due to physical wear and tear.

Robust System Operation

To over come this problem new approaches to be implemented for a robust system operation.

This means Developing reliable code, debugging techniques, fault tolerant and general health monitoring services

Openness: Mostly sensor based systems are closed systems. Ex: cars , airplanes etc. These systems and other WSAN systems are expanding rapidly .

General info about these cars and airplane such as maintenance information is sent to manufactures through sensors.

WSANs will enable an even greater cooperation and 2-way control on a wide scale: cars (and aircraft) talking to each other and controlling each other to avoid collisions, humans exchanging data automatically when they meet and this possibly affecting their next actions, and physiological data uploaded to doctors in real time with real-time feedback from the doctor.

Human interaction is an integral aspect of openness, and this makes modeling extremely difficult. The scaling and interactions across systems also dynamically change the models and create a need for decentralized control. While some work has been performed in areas such as stochastic, robust, distributed, and adaptive control, these areas are not developed well enough to support the degree of openness and dynamics expected in WSAN.

Major problem with WSAN is dealing with security attacks. This is a critical issue because of minimal capacity devices . Permanent random failures. Redundancy in WSAN design to work even in face of failure.

Security attacks and recovery from attacks. Strong detection capabilities – detect, diagnose, deploy

countermeasures . self-healing features-better than complete secure system. Mainframes Security solution are heavyweight

computations which is major challenge. Quick response. Healing with reprogramming.

Security

opportunities to violate privacy privacy policies for domains. System decision for granted or denied. Requirements: context information- time, space, physiological sensing, environmental sensing, and stream-based noisy

data Evaluate data requester. Need to represent high-level aggregating requests-

avg ,min,max etc. Privacy on request to parameters . allow dynamic changes to the policies and keep track of

dependents. Major problem- interacting with other systems, each having

own privacy policies.

Privacy

This paper focuses on future applications and research. For readers interested in the individual open research questions discussed, those particular sections contain references to related works. This section presents several additional comprehensive papers related to WSAN

Related Work

When WSANs cover the world, a new revolution similar to the Industrial and Internet revolutions will occur. But robustness, security, and privacy to co-exist—not an easy task!

Many other important topics targeting WSAN must also be addressed including the following: heterogeneity, standards, programming abstractions and languages, real-time stream databases, middleware, operating systems, scaling, composition theory and analysis, formal methods, the wireless spectrum, wireless realities including interference, real-time, system safety, design, analysis and debugging tools, energy scavenging and power control, mobility, time synchronization, location services, decentralized algorithms, swarm computing, and signal processing. Simultaneously addressing several of these issues in the context of WSAN will produce many interesting research problems.

Conclusion

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